Loss of Natriuretic Peptide Receptor C Enhances Sinoatrial Node Dysfunction in Aging and Frail Mice
Bibliographic record
Abstract
Heart rate (HR) is controlled by the sinoatrial node (SAN). SAN dysfunction is highly prevalent in aging; however, not all individuals age at the same rate. Rather, health status during aging is affected by frailty. Natriuretic peptides regulate SAN function in part by activating natriuretic peptide receptor C (NPR-C). The impacts of NPR-C on HR and SAN function in aging and as a function of frailty are unknown. Frailty was measured in aging wild-type and NPR-C knockout (NPR-C-/-) mice using a mouse clinical frailty index (FI). HR and SAN structure and function were investigated using intracardiac electrophysiology in anesthetized mice, high-resolution optical mapping in intact atrial preparations, histology, and molecular biology. NPR-C-/- mice rapidly became frail leading to shortened life span. HR was reduced and SAN recovery time was increased in older versus younger mice, and these changes were exacerbated in NPR-C-/- mice; however, there was substantial variability among age groups and genotypes. HR and SAN recovery time were correlated with FI score and fell along a continuum regardless of age or genotype. Optical mapping demonstrates impairments in SAN function that were also correlated with FI score. SAN fibrosis was increased in aged and NPR-C-/- mice and was graded by FI score. Loss of NPR-C results in accelerated aging and rapid decline in health status in association with impairments in HR and SAN function. Frailty assessment was effective and better able to distinguish aging-dependent changes in SAN function in the setting of shortened life span due to loss of NPR-C.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".